Seeking Lift Monitoring and Diagnostic System

Background / Description

There is currently a lift monitoring system in place to monitor lift operations and manage emergency events, for example man-trap cases. However, the current lift monitoring system does not provide sufficient information that could translate to meaningful diagnostics of lift faults. Moreover, lift fault diagnosis and rectification has to be done manually by the maintenance crew on site. Manpower demands for lift technicians are increasing with the growth in the number of lifts; whilst manpower supply is dwindling as our workforce ages. With aging infrastructure and a shortage of lift maintenance professionals, there is an urgent need to improve the productivity of this industry through the efficient use of technology.

One way to improve productivity is through the implementation of a Remote Monitoring & Diagnostics System. Whilst some of the major Original Equipment Manufacturers (OEMs) have these technical capabilities, it is costly for lift owners to procure such services. Furthermore, for lift owners with multiple brands of lifts, it is not cost-effective and efficient to use multiple lift remote monitoring systems. Having a 3rd party Remote Monitoring & Diagnostics System in the market will provide lift owners with a one-stop solution for their lifts. However, it is not easy to differentiate and assess them because there are many variations in their solutioning available in the market. In addition, their solutioning capabilities are still relatively unknown when compared to that of the OEM counterparts. It is therefore important to conduct research to develop an integrated 3rd party remote monitoring and diagnostics system.

Technical Specifications


The objectives of the project are to:

  • Develop a 3rd party Remote Monitoring and Diagnostics System that integrates requirements and functionalities of a variety of current lift technologies, as well as improves the accuracy of lift fault diagnosis, allowing predictive and proactive maintenance. This System should be comparable to or better than OEM systems in terms of monitoring methods and prediction analysis;
  • Leverage Smart Technology and AI to improve lift monitoring and performance; and
  • Identify and develop a common standard for Remote Monitoring & Diagnostics System to allow any 3rd party solution provider to develop such remote monitoring and diagnostics solutions for the market.


  • Principal Investigators (PIs) from all Singapore-based institutions of higher learning (IHLs), public sector agencies and not-for-profit research laboratories as well as companies and company-affiliated research laboratories/institutions, are eligible to apply.
  • The Lead PI who leads the Research must be based in Singapore. Collaboration with foreign organisations and experts in the capacity of Co-Principal Investigator (Co-PI), or as Collaborator is allowed.
  • Research work should be done in Singapore, and should not be carried out overseas unless expressly approved by the grantor.
  • The proposals must not have obtained similar funding from other government agencies. Proposals with similar scope, which are currently under evaluation by other funding initiatives, would not be considered until the results from the other funding initiatives are finalized.
  • Grant applicants are strongly encouraged to collaborate with industry and development agencies to develop innovative solutions that can address the call objectives and demonstrate strong potential for real-world application within Singapore.

Submission Instructions

Details of the CFP are attached herewith. Please download all files and read all instructions and guidelines for the Grant Call by clicking on the <<Proceed to Details>> button below.

All proposals must be submitted to both and by 19 Jul 2018, 2359 hrs. Late submissions or submissions from individual applicants without endorsement from the Host Institution will not be entertained.

In case of conflicting information, the Grant Call website shall be taken as most updated source.

Preferred Business Model

  • R&D Collaboration

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